Overview

Brought to you by YData

Dataset statistics

Number of variables19
Number of observations37500
Missing cells111133
Missing cells (%)15.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 MiB
Average record size in memory152.0 B

Variable types

Numeric12
Text5
DateTime1
Categorical1

Alerts

review/appearance is highly overall correlated with review/palateHigh correlation
review/aroma is highly overall correlated with review/overall and 2 other fieldsHigh correlation
review/overall is highly overall correlated with review/aroma and 2 other fieldsHigh correlation
review/palate is highly overall correlated with review/appearance and 3 other fieldsHigh correlation
review/taste is highly overall correlated with review/aroma and 2 other fieldsHigh correlation
user/ageInSeconds is highly overall correlated with user/birthdayUnixHigh correlation
user/birthdayUnix is highly overall correlated with user/ageInSecondsHigh correlation
user/gender is highly imbalanced (88.2%) Imbalance
user/ageInSeconds has 29644 (79.1%) missing values Missing
user/birthdayRaw has 29644 (79.1%) missing values Missing
user/birthdayUnix has 29644 (79.1%) missing values Missing
user/gender has 22186 (59.2%) missing values Missing
df_index is uniformly distributed Uniform
df_index has unique values Unique

Reproduction

Analysis started2024-11-13 17:28:47.331295
Analysis finished2024-11-13 17:29:33.231306
Duration45.9 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

df_index
Real number (ℝ)

Uniform  Unique 

Distinct37500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24951.888
Minimum0
Maximum49999
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:33.460189image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2495.95
Q112422.5
median24942.5
Q337416.75
95-th percentile47482.1
Maximum49999
Range49999
Interquartile range (IQR)24994.25

Descriptive statistics

Standard deviation14434.01
Coefficient of variation (CV)0.57847366
Kurtosis-1.2005239
Mean24951.888
Median Absolute Deviation (MAD)12497
Skewness0.0023210834
Sum9.3569578 × 108
Variance2.0834064 × 108
MonotonicityNot monotonic
2024-11-13T12:29:33.746025image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40163 1
 
< 0.1%
38112 1
 
< 0.1%
23470 1
 
< 0.1%
3776 1
 
< 0.1%
30174 1
 
< 0.1%
22375 1
 
< 0.1%
5080 1
 
< 0.1%
39079 1
 
< 0.1%
38353 1
 
< 0.1%
13419 1
 
< 0.1%
Other values (37490) 37490
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
49999 1
< 0.1%
49998 1
< 0.1%
49997 1
< 0.1%
49996 1
< 0.1%
49994 1
< 0.1%
49993 1
< 0.1%
49992 1
< 0.1%
49991 1
< 0.1%
49990 1
< 0.1%
49988 1
< 0.1%

beer/ABV
Real number (ℝ)

Distinct126
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4037248
Minimum0.1
Maximum57.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:34.364655image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.4
Q15.4
median6.9
Q39.4
95-th percentile11.2
Maximum57.7
Range57.6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3181453
Coefficient of variation (CV)0.31310528
Kurtosis9.1537636
Mean7.4037248
Median Absolute Deviation (MAD)1.6
Skewness0.94168799
Sum277639.68
Variance5.3737978
MonotonicityNot monotonic
2024-11-13T12:29:34.654503image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.5 2096
 
5.6%
5 2015
 
5.4%
8.3 1890
 
5.0%
6.6 1848
 
4.9%
9.4 1847
 
4.9%
5.4 1711
 
4.6%
12 1500
 
4.0%
11.2 1441
 
3.8%
8.5 1349
 
3.6%
4.4 1341
 
3.6%
Other values (116) 20462
54.6%
ValueCountFrequency (%)
0.1 2
 
< 0.1%
0.5 2
 
< 0.1%
1.5 3
 
< 0.1%
2.2 2
 
< 0.1%
2.4 6
< 0.1%
2.5 2
 
< 0.1%
2.8 8
< 0.1%
3 9
< 0.1%
3.1 6
< 0.1%
3.2 1
 
< 0.1%
ValueCountFrequency (%)
57.7 1
 
< 0.1%
43 2
 
< 0.1%
39.44 1
 
< 0.1%
30.86 1
 
< 0.1%
16 7
 
< 0.1%
15 13
 
< 0.1%
14.5 1
 
< 0.1%
14 6
 
< 0.1%
13 101
0.3%
12.9 4
 
< 0.1%

beer/beerId
Real number (ℝ)

Distinct1731
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21861.152
Minimum175
Maximum77207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:34.936341image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum175
5-th percentile727
Q15441
median17538
Q334146
95-th percentile58053
Maximum77207
Range77032
Interquartile range (IQR)28705

Descriptive statistics

Standard deviation18923.131
Coefficient of variation (CV)0.86560538
Kurtosis-0.31886527
Mean21861.152
Median Absolute Deviation (MAD)13524
Skewness0.79963188
Sum8.197932 × 108
Variance3.5808488 × 108
MonotonicityNot monotonic
2024-11-13T12:29:35.247148image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11757 1883
 
5.0%
19960 1441
 
3.8%
5441 1064
 
2.8%
16074 1051
 
2.8%
7463 983
 
2.6%
429 947
 
2.5%
34146 857
 
2.3%
21822 805
 
2.1%
17538 800
 
2.1%
35036 778
 
2.1%
Other values (1721) 26891
71.7%
ValueCountFrequency (%)
175 56
 
0.1%
176 92
 
0.2%
178 68
 
0.2%
429 947
2.5%
436 345
 
0.9%
454 21
 
0.1%
503 1
 
< 0.1%
505 26
 
0.1%
507 29
 
0.1%
508 2
 
< 0.1%
ValueCountFrequency (%)
77207 1
< 0.1%
77199 1
< 0.1%
77198 1
< 0.1%
77116 1
< 0.1%
76999 1
< 0.1%
76998 1
< 0.1%
76997 2
< 0.1%
76996 2
< 0.1%
76995 2
< 0.1%
76963 1
< 0.1%

beer/brewerId
Real number (ℝ)

Distinct212
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3036.5951
Minimum1
Maximum27797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:35.536996image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile60
Q1395
median1199
Q31315
95-th percentile14879
Maximum27797
Range27796
Interquartile range (IQR)920

Descriptive statistics

Standard deviation5123.0847
Coefficient of variation (CV)1.6871148
Kurtosis4.5749629
Mean3036.5951
Median Absolute Deviation (MAD)625
Skewness2.3536643
Sum1.1387232 × 108
Variance26245997
MonotonicityNot monotonic
2024-11-13T12:29:35.803842image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1199 14976
39.9%
394 2937
 
7.8%
14879 2351
 
6.3%
263 1809
 
4.8%
3268 1277
 
3.4%
395 1226
 
3.3%
365 1069
 
2.9%
1 1017
 
2.7%
1417 908
 
2.4%
14 834
 
2.2%
Other values (202) 9096
24.3%
ValueCountFrequency (%)
1 1017
 
2.7%
14 834
 
2.2%
60 451
 
1.2%
163 427
 
1.1%
263 1809
4.8%
289 55
 
0.1%
365 1069
 
2.9%
394 2937
7.8%
395 1226
3.3%
453 76
 
0.2%
ValueCountFrequency (%)
27797 2
 
< 0.1%
27133 1
 
< 0.1%
27079 1
 
< 0.1%
27021 2
 
< 0.1%
26990 15
< 0.1%
26983 1
 
< 0.1%
26946 6
 
< 0.1%
26816 6
 
< 0.1%
26612 6
 
< 0.1%
26409 1
 
< 0.1%
Distinct1688
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:36.207616image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length72
Median length51
Mean length23.02688
Min length2

Characters and Unicode

Total characters863508
Distinct characters112
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique616 ?
Unique (%)1.6%

Sample

1st rowChiostro
2nd rowBearded Pat's Barleywine
3rd rowNaughty Nellie's Ale
4th rowPilsner Urquell
5th rowBlack Sheep Ale (Special)
ValueCountFrequency (%)
founders 14976
 
12.0%
stout 7222
 
5.8%
ale 6620
 
5.3%
breakfast 3334
 
2.7%
ipa 3014
 
2.4%
pale 2494
 
2.0%
double 2379
 
1.9%
imperial 2344
 
1.9%
porter 2156
 
1.7%
stoudt's 1831
 
1.5%
Other values (1933) 78132
62.8%
2024-11-13T12:29:36.979174image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 91610
 
10.6%
87048
 
10.1%
r 60437
 
7.0%
o 48520
 
5.6%
t 46378
 
5.4%
a 45167
 
5.2%
l 40985
 
4.7%
u 39475
 
4.6%
s 39011
 
4.5%
n 38429
 
4.5%
Other values (102) 326448
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 603856
69.9%
Uppercase Letter 144808
 
16.8%
Space Separator 87048
 
10.1%
Other Punctuation 12081
 
1.4%
Decimal Number 4433
 
0.5%
Close Punctuation 3973
 
0.5%
Open Punctuation 3973
 
0.5%
Dash Punctuation 1657
 
0.2%
Currency Symbol 700
 
0.1%
Other Symbol 421
 
< 0.1%
Other values (7) 558
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 20058
13.9%
F 16515
11.4%
B 16351
11.3%
A 15982
11.0%
P 13118
9.1%
I 8592
 
5.9%
D 7117
 
4.9%
R 6843
 
4.7%
C 5574
 
3.8%
O 4768
 
3.3%
Other values (20) 29890
20.6%
Lowercase Letter
ValueCountFrequency (%)
e 91610
15.2%
r 60437
10.0%
o 48520
 
8.0%
t 46378
 
7.7%
a 45167
 
7.5%
l 40985
 
6.8%
u 39475
 
6.5%
s 39011
 
6.5%
n 38429
 
6.4%
d 29243
 
4.8%
Other values (17) 124601
20.6%
Other Punctuation
ValueCountFrequency (%)
. 6888
57.0%
' 4567
37.8%
¡ 256
 
2.1%
& 139
 
1.2%
# 55
 
0.5%
" 46
 
0.4%
; 36
 
0.3%
: 21
 
0.2%
% 21
 
0.2%
, 20
 
0.2%
Other values (3) 32
 
0.3%
Control
ValueCountFrequency (%)
œ 35
30.2%
Ž 33
28.4%
ž 28
24.1%
š 4
 
3.4%
’ 4
 
3.4%
€ 3
 
2.6%
‰ 2
 
1.7%
˜ 2
 
1.7%
Ÿ 1
 
0.9%
 1
 
0.9%
Other values (3) 3
 
2.6%
Decimal Number
ValueCountFrequency (%)
0 1766
39.8%
2 900
20.3%
1 665
 
15.0%
5 448
 
10.1%
9 426
 
9.6%
7 109
 
2.5%
6 52
 
1.2%
3 32
 
0.7%
8 21
 
0.5%
4 14
 
0.3%
Other Number
ValueCountFrequency (%)
¼ 237
91.5%
½ 15
 
5.8%
³ 6
 
2.3%
¾ 1
 
0.4%
Other Symbol
ValueCountFrequency (%)
¦ 215
51.1%
© 191
45.4%
° 15
 
3.6%
Currency Symbol
ValueCountFrequency (%)
¤ 697
99.6%
¥ 3
 
0.4%
Modifier Symbol
ValueCountFrequency (%)
¨ 34
50.7%
¸ 33
49.3%
Space Separator
ValueCountFrequency (%)
87048
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3973
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3973
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1657
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 91
100.0%
Format
ValueCountFrequency (%)
­ 20
100.0%
Math Symbol
ValueCountFrequency (%)
± 4
100.0%
Other Letter
ValueCountFrequency (%)
ª 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 748665
86.7%
Common 114843
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 91610
 
12.2%
r 60437
 
8.1%
o 48520
 
6.5%
t 46378
 
6.2%
a 45167
 
6.0%
l 40985
 
5.5%
u 39475
 
5.3%
s 39011
 
5.2%
n 38429
 
5.1%
d 29243
 
3.9%
Other values (48) 269410
36.0%
Common
ValueCountFrequency (%)
87048
75.8%
. 6888
 
6.0%
' 4567
 
4.0%
) 3973
 
3.5%
( 3973
 
3.5%
0 1766
 
1.5%
- 1657
 
1.4%
2 900
 
0.8%
¤ 697
 
0.6%
1 665
 
0.6%
Other values (44) 2709
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 859615
99.5%
None 3893
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 91610
 
10.7%
87048
 
10.1%
r 60437
 
7.0%
o 48520
 
5.6%
t 46378
 
5.4%
a 45167
 
5.3%
l 40985
 
4.8%
u 39475
 
4.6%
s 39011
 
4.5%
n 38429
 
4.5%
Other values (67) 322555
37.5%
None
ValueCountFrequency (%)
à 1856
47.7%
¤ 697
 
17.9%
¡ 256
 
6.6%
¼ 237
 
6.1%
¦ 215
 
5.5%
© 191
 
4.9%
« 91
 
2.3%
 84
 
2.2%
œ 35
 
0.9%
¨ 34
 
0.9%
Other values (25) 197
 
5.1%
Distinct95
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:37.308985image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length35
Median length28
Mean length19.10184
Min length4

Characters and Unicode

Total characters716319
Distinct characters58
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHerbed / Spiced Beer
2nd rowAmerican Barleywine
3rd rowAmerican Pale Ale (APA)
4th rowCzech Pilsener
5th rowEnglish Pale Ale
ValueCountFrequency (%)
american 16708
14.1%
12591
 
10.6%
imperial 9409
 
7.9%
ale 9200
 
7.7%
double 7377
 
6.2%
stout 7327
 
6.2%
ipa 6141
 
5.2%
pale 4105
 
3.5%
beer 2505
 
2.1%
porter 2359
 
2.0%
Other values (103) 40988
34.5%
2024-11-13T12:29:37.931606image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 86523
 
12.1%
81210
 
11.3%
r 48806
 
6.8%
a 44921
 
6.3%
i 41982
 
5.9%
l 41894
 
5.8%
A 36329
 
5.1%
n 30485
 
4.3%
m 28023
 
3.9%
t 27948
 
3.9%
Other values (48) 248198
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 493857
68.9%
Uppercase Letter 123322
 
17.2%
Space Separator 81210
 
11.3%
Other Punctuation 12655
 
1.8%
Open Punctuation 2424
 
0.3%
Close Punctuation 2424
 
0.3%
Currency Symbol 410
 
0.1%
Dash Punctuation 13
 
< 0.1%
Modifier Symbol 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 86523
17.5%
r 48806
9.9%
a 44921
9.1%
i 41982
8.5%
l 41894
8.5%
n 30485
 
6.2%
m 28023
 
5.7%
t 27948
 
5.7%
c 26925
 
5.5%
o 25325
 
5.1%
Other values (16) 91025
18.4%
Uppercase Letter
ValueCountFrequency (%)
A 36329
29.5%
P 16327
13.2%
I 15809
12.8%
S 12440
 
10.1%
D 8767
 
7.1%
B 7153
 
5.8%
R 5428
 
4.4%
E 4234
 
3.4%
H 3379
 
2.7%
W 3213
 
2.6%
Other values (13) 10243
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 12481
98.6%
& 97
 
0.8%
77
 
0.6%
Space Separator
ValueCountFrequency (%)
81210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2424
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2424
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 410
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 617179
86.2%
Common 99140
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 86523
14.0%
r 48806
 
7.9%
a 44921
 
7.3%
i 41982
 
6.8%
l 41894
 
6.8%
A 36329
 
5.9%
n 30485
 
4.9%
m 28023
 
4.5%
t 27948
 
4.5%
c 26925
 
4.4%
Other values (39) 203343
32.9%
Common
ValueCountFrequency (%)
81210
81.9%
/ 12481
 
12.6%
( 2424
 
2.4%
) 2424
 
2.4%
¤ 410
 
0.4%
& 97
 
0.1%
77
 
0.1%
- 13
 
< 0.1%
¨ 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 715337
99.9%
None 982
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 86523
 
12.1%
81210
 
11.4%
r 48806
 
6.8%
a 44921
 
6.3%
i 41982
 
5.9%
l 41894
 
5.9%
A 36329
 
5.1%
n 30485
 
4.3%
m 28023
 
3.9%
t 27948
 
3.9%
Other values (44) 247216
34.6%
None
ValueCountFrequency (%)
à 491
50.0%
¤ 410
41.8%
77
 
7.8%
¨ 4
 
0.4%

review/appearance
Real number (ℝ)

High correlation 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9000533
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:38.169468image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q13.5
median4
Q34.5
95-th percentile4.5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.58877832
Coefficient of variation (CV)0.15096674
Kurtosis1.5151779
Mean3.9000533
Median Absolute Deviation (MAD)0.5
Skewness-0.79263521
Sum146252
Variance0.34665991
MonotonicityNot monotonic
2024-11-13T12:29:38.373365image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 16058
42.8%
4.5 7597
20.3%
3.5 7224
19.3%
3 3396
 
9.1%
5 1862
 
5.0%
2.5 807
 
2.2%
2 437
 
1.2%
1.5 84
 
0.2%
1 34
 
0.1%
0 1
 
< 0.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 34
 
0.1%
1.5 84
 
0.2%
2 437
 
1.2%
2.5 807
 
2.2%
3 3396
 
9.1%
3.5 7224
19.3%
4 16058
42.8%
4.5 7597
20.3%
5 1862
 
5.0%
ValueCountFrequency (%)
5 1862
 
5.0%
4.5 7597
20.3%
4 16058
42.8%
3.5 7224
19.3%
3 3396
 
9.1%
2.5 807
 
2.2%
2 437
 
1.2%
1.5 84
 
0.2%
1 34
 
0.1%
0 1
 
< 0.1%

review/aroma
Real number (ℝ)

High correlation 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.87324
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:38.611212image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.68086533
Coefficient of variation (CV)0.17578702
Kurtosis1.166439
Mean3.87324
Median Absolute Deviation (MAD)0.5
Skewness-0.83016929
Sum145246.5
Variance0.4635776
MonotonicityNot monotonic
2024-11-13T12:29:38.827087image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 13034
34.8%
4.5 8407
22.4%
3.5 7473
19.9%
3 3855
 
10.3%
5 2579
 
6.9%
2.5 1094
 
2.9%
2 773
 
2.1%
1.5 195
 
0.5%
1 90
 
0.2%
ValueCountFrequency (%)
1 90
 
0.2%
1.5 195
 
0.5%
2 773
 
2.1%
2.5 1094
 
2.9%
3 3855
 
10.3%
3.5 7473
19.9%
4 13034
34.8%
4.5 8407
22.4%
5 2579
 
6.9%
ValueCountFrequency (%)
5 2579
 
6.9%
4.5 8407
22.4%
4 13034
34.8%
3.5 7473
19.9%
3 3855
 
10.3%
2.5 1094
 
2.9%
2 773
 
2.1%
1.5 195
 
0.5%
1 90
 
0.2%

review/overall
Real number (ℝ)

High correlation 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.88944
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:39.054958image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.70044955
Coefficient of variation (CV)0.18009008
Kurtosis1.7430682
Mean3.88944
Median Absolute Deviation (MAD)0.5
Skewness-1.0401798
Sum145854
Variance0.49062957
MonotonicityNot monotonic
2024-11-13T12:29:39.272848image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 13868
37.0%
4.5 8666
23.1%
3.5 6551
17.5%
3 3319
 
8.9%
5 2671
 
7.1%
2.5 1193
 
3.2%
2 807
 
2.2%
1.5 248
 
0.7%
1 176
 
0.5%
0 1
 
< 0.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 176
 
0.5%
1.5 248
 
0.7%
2 807
 
2.2%
2.5 1193
 
3.2%
3 3319
 
8.9%
3.5 6551
17.5%
4 13868
37.0%
4.5 8666
23.1%
5 2671
 
7.1%
ValueCountFrequency (%)
5 2671
 
7.1%
4.5 8666
23.1%
4 13868
37.0%
3.5 6551
17.5%
3 3319
 
8.9%
2.5 1193
 
3.2%
2 807
 
2.2%
1.5 248
 
0.7%
1 176
 
0.5%
0 1
 
< 0.1%

review/palate
Real number (ℝ)

High correlation 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8548667
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:39.485711image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.66806802
Coefficient of variation (CV)0.17330509
Kurtosis1.333727
Mean3.8548667
Median Absolute Deviation (MAD)0.5
Skewness-0.83914236
Sum144557.5
Variance0.44631488
MonotonicityNot monotonic
2024-11-13T12:29:39.744560image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 14606
38.9%
4.5 7225
19.3%
3.5 7082
18.9%
3 4007
 
10.7%
5 2422
 
6.5%
2.5 1161
 
3.1%
2 709
 
1.9%
1.5 189
 
0.5%
1 99
 
0.3%
ValueCountFrequency (%)
1 99
 
0.3%
1.5 189
 
0.5%
2 709
 
1.9%
2.5 1161
 
3.1%
3 4007
 
10.7%
3.5 7082
18.9%
4 14606
38.9%
4.5 7225
19.3%
5 2422
 
6.5%
ValueCountFrequency (%)
5 2422
 
6.5%
4.5 7225
19.3%
4 14606
38.9%
3.5 7082
18.9%
3 4007
 
10.7%
2.5 1161
 
3.1%
2 709
 
1.9%
1.5 189
 
0.5%
1 99
 
0.3%

review/taste
Real number (ℝ)

High correlation 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.92244
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:39.969449image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.71650411
Coefficient of variation (CV)0.18266796
Kurtosis1.4582962
Mean3.92244
Median Absolute Deviation (MAD)0.5
Skewness-1.0004504
Sum147091.5
Variance0.51337814
MonotonicityNot monotonic
2024-11-13T12:29:40.200316image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 12381
33.0%
4.5 9684
25.8%
3.5 6577
17.5%
5 3259
 
8.7%
3 3141
 
8.4%
2.5 1232
 
3.3%
2 817
 
2.2%
1.5 258
 
0.7%
1 151
 
0.4%
ValueCountFrequency (%)
1 151
 
0.4%
1.5 258
 
0.7%
2 817
 
2.2%
2.5 1232
 
3.3%
3 3141
 
8.4%
3.5 6577
17.5%
4 12381
33.0%
4.5 9684
25.8%
5 3259
 
8.7%
ValueCountFrequency (%)
5 3259
 
8.7%
4.5 9684
25.8%
4 12381
33.0%
3.5 6577
17.5%
3 3141
 
8.4%
2.5 1232
 
3.3%
2 817
 
2.2%
1.5 258
 
0.7%
1 151
 
0.4%
Distinct37482
Distinct (%)> 99.9%
Missing10
Missing (%)< 0.1%
Memory size293.1 KiB
2024-11-13T12:29:40.651059image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length4721
Median length2031
Mean length719.07775
Min length49

Characters and Unicode

Total characters26958225
Distinct characters94
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37474 ?
Unique (%)> 99.9%

Sample

1st rowPours a clouded gold with a thin white head. Nose is quite floral with a larger amount of spices added. Definitely a spice forward fragrance. Flavor has an odd burn that hits on the first sip. After it fades it seems like a dirty vanilla aftertaste. Perhaps this is the absinthe? Regardless of that, I get a quite spiced tone on the tongue. Almost feel a little heat from it. I think that my inexperienced palate on these spices is contributing to my ignorance of what precisely they are. Overall a nice drinker indeed.
2nd row12oz bottle into 8oz snifter. Deep ruby red hue with a one finger light tan head that settles to a thin rim along the glass. Sharp piercing hops with some light hard candy in the background. The hops provide some bitterness, but they aren't as sharp as I would have expected. Mostly a light candy flavor like in the aroma. Full bodied with good carbonation. The finish is some lingering sweet flavor with a bit of bitterness. A very sweet barleywine with a weird hard candy flavor that seemed to dominate. Not bad, but I would have liked a little more complexity.
3rd rowFirst enjoyed at the brewpub about 2 years ago, I finally managed to get a bottle. Slightly hazy orange-amber topped with a two finger foamy white head. Very nice fruity aroma, soft and floral, tea and toast. Fruity, slightly grapefruity hop note, toast and biscuity malt balance. Hoppier and more floral when it warms up. Light-medium bodied, liked it better on draft but still a solid beer.
4th rowFirst thing I noticed after pouring from green bottle to glass was the skunky smell. Overpowering. Lacing was minimal and faded quickly. Bottle had exp date and was still within freshness date. Taste was like drinking a milwaukee's best with some skunk. Just couldn't get over the skunky smell to finish my second bottle. Almost $10 a sixer, I would have been better off getting Bud Light.
5th rowA: pours an amber with a one finger head but only with a very strong pour, head recedes to a light layer of foam with some large bubbles and good lacing S: sweet caramel and bread from the English malts comes through, some mild fruityness on the back end T: not a lot of complexity with this for me. I didn't expect much considering the style but it's just bland and lacking more bready layers M/D: more carbonated than I would have wanted. I would expect this to be much better on cask
ValueCountFrequency (%)
a 231704
 
4.8%
the 209065
 
4.4%
and 146195
 
3.0%
of 119908
 
2.5%
is 96485
 
2.0%
with 86272
 
1.8%
to 72600
 
1.5%
this 69684
 
1.5%
i 64118
 
1.3%
it 60584
 
1.3%
Other values (67211) 3647137
75.9%
2024-11-13T12:29:41.407624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4671408
17.3%
e 2375207
 
8.8%
t 1964862
 
7.3%
a 1744284
 
6.5%
o 1587205
 
5.9%
i 1426484
 
5.3%
s 1332303
 
4.9%
n 1221863
 
4.5%
r 1196646
 
4.4%
l 1081222
 
4.0%
Other values (84) 8356741
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20395548
75.7%
Space Separator 4671408
 
17.3%
Other Punctuation 836523
 
3.1%
Uppercase Letter 659430
 
2.4%
Control 225425
 
0.8%
Decimal Number 76392
 
0.3%
Dash Punctuation 68992
 
0.3%
Close Punctuation 10907
 
< 0.1%
Open Punctuation 10459
 
< 0.1%
Math Symbol 1585
 
< 0.1%
Other values (3) 1556
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2375207
11.6%
t 1964862
 
9.6%
a 1744284
 
8.6%
o 1587205
 
7.8%
i 1426484
 
7.0%
s 1332303
 
6.5%
n 1221863
 
6.0%
r 1196646
 
5.9%
l 1081222
 
5.3%
h 1046549
 
5.1%
Other values (16) 5418923
26.6%
Uppercase Letter
ValueCountFrequency (%)
I 109918
16.7%
T 99159
15.0%
A 71370
10.8%
S 55928
 
8.5%
P 37795
 
5.7%
M 35388
 
5.4%
B 33195
 
5.0%
D 27011
 
4.1%
N 21448
 
3.3%
F 20492
 
3.1%
Other values (16) 147726
22.4%
Other Punctuation
ValueCountFrequency (%)
. 434808
52.0%
, 247587
29.6%
' 60502
 
7.2%
: 38858
 
4.6%
/ 15194
 
1.8%
! 12762
 
1.5%
" 8834
 
1.1%
; 5412
 
0.6%
? 4328
 
0.5%
% 4270
 
0.5%
Other values (5) 3968
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 17982
23.5%
2 16128
21.1%
0 14482
19.0%
5 6653
 
8.7%
4 4759
 
6.2%
9 3997
 
5.2%
3 3995
 
5.2%
6 3079
 
4.0%
8 2720
 
3.6%
7 2597
 
3.4%
Math Symbol
ValueCountFrequency (%)
= 744
46.9%
+ 521
32.9%
~ 168
 
10.6%
| 152
 
9.6%
Close Punctuation
ValueCountFrequency (%)
) 10801
99.0%
] 105
 
1.0%
} 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 10351
99.0%
[ 106
 
1.0%
{ 2
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 33
61.1%
^ 21
38.9%
Space Separator
ValueCountFrequency (%)
4671408
100.0%
Control
ValueCountFrequency (%)
225425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68992
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1274
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21054978
78.1%
Common 5903247
 
21.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2375207
 
11.3%
t 1964862
 
9.3%
a 1744284
 
8.3%
o 1587205
 
7.5%
i 1426484
 
6.8%
s 1332303
 
6.3%
n 1221863
 
5.8%
r 1196646
 
5.7%
l 1081222
 
5.1%
h 1046549
 
5.0%
Other values (42) 6078353
28.9%
Common
ValueCountFrequency (%)
4671408
79.1%
. 434808
 
7.4%
, 247587
 
4.2%
225425
 
3.8%
- 68992
 
1.2%
' 60502
 
1.0%
: 38858
 
0.7%
1 17982
 
0.3%
2 16128
 
0.3%
/ 15194
 
0.3%
Other values (32) 106363
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26958225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4671408
17.3%
e 2375207
 
8.8%
t 1964862
 
7.3%
a 1744284
 
6.5%
o 1587205
 
5.9%
i 1426484
 
5.3%
s 1332303
 
4.9%
n 1221863
 
4.5%
r 1196646
 
4.4%
l 1081222
 
4.0%
Other values (84) 8356741
31.0%
Distinct37490
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:41.721447image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length107
Median length106
Mean length104.81691
Min length100

Characters and Unicode

Total characters3930634
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37482 ?
Unique (%)> 99.9%

Sample

1st row{'min': 38, 'hour': 3, 'mday': 16, 'sec': 10, 'year': 2008, 'wday': 1, 'mon': 12, 'isdst': 0, 'yday': 351}
2nd row{'min': 38, 'hour': 23, 'mday': 8, 'sec': 58, 'year': 2008, 'wday': 4, 'mon': 8, 'isdst': 0, 'yday': 221}
3rd row{'min': 7, 'hour': 18, 'mday': 26, 'sec': 2, 'year': 2004, 'wday': 4, 'mon': 11, 'isdst': 0, 'yday': 331}
4th row{'min': 7, 'hour': 1, 'mday': 20, 'sec': 5, 'year': 2011, 'wday': 0, 'mon': 6, 'isdst': 0, 'yday': 171}
5th row{'min': 51, 'hour': 6, 'mday': 12, 'sec': 48, 'year': 2011, 'wday': 5, 'mon': 3, 'isdst': 0, 'yday': 71}
ValueCountFrequency (%)
0 47189
 
7.0%
min 37500
 
5.6%
year 37500
 
5.6%
yday 37500
 
5.6%
isdst 37500
 
5.6%
mon 37500
 
5.6%
wday 37500
 
5.6%
sec 37500
 
5.6%
mday 37500
 
5.6%
hour 37500
 
5.6%
Other values (380) 290311
43.0%
2024-11-13T12:29:42.303113image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 675000
17.2%
637500
16.2%
: 337500
 
8.6%
, 300000
 
7.6%
y 187500
 
4.8%
a 150000
 
3.8%
d 150000
 
3.8%
0 135730
 
3.5%
2 118581
 
3.0%
1 116029
 
3.0%
Other values (21) 1122794
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 1312500
33.4%
Lowercase Letter 1275000
32.4%
Space Separator 637500
16.2%
Decimal Number 630634
16.0%
Close Punctuation 37500
 
1.0%
Open Punctuation 37500
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
y 187500
14.7%
a 150000
11.8%
d 150000
11.8%
m 112500
8.8%
s 112500
8.8%
o 75000
 
5.9%
r 75000
 
5.9%
n 75000
 
5.9%
i 75000
 
5.9%
e 75000
 
5.9%
Other values (5) 187500
14.7%
Decimal Number
ValueCountFrequency (%)
0 135730
21.5%
2 118581
18.8%
1 116029
18.4%
3 56574
9.0%
5 44232
 
7.0%
4 44225
 
7.0%
6 32300
 
5.1%
9 29354
 
4.7%
8 27686
 
4.4%
7 25923
 
4.1%
Other Punctuation
ValueCountFrequency (%)
' 675000
51.4%
: 337500
25.7%
, 300000
22.9%
Space Separator
ValueCountFrequency (%)
637500
100.0%
Close Punctuation
ValueCountFrequency (%)
} 37500
100.0%
Open Punctuation
ValueCountFrequency (%)
{ 37500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2655634
67.6%
Latin 1275000
32.4%

Most frequent character per script

Common
ValueCountFrequency (%)
' 675000
25.4%
637500
24.0%
: 337500
12.7%
, 300000
11.3%
0 135730
 
5.1%
2 118581
 
4.5%
1 116029
 
4.4%
3 56574
 
2.1%
5 44232
 
1.7%
4 44225
 
1.7%
Other values (6) 190263
 
7.2%
Latin
ValueCountFrequency (%)
y 187500
14.7%
a 150000
11.8%
d 150000
11.8%
m 112500
8.8%
s 112500
8.8%
o 75000
 
5.9%
r 75000
 
5.9%
n 75000
 
5.9%
i 75000
 
5.9%
e 75000
 
5.9%
Other values (5) 187500
14.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3930634
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 675000
17.2%
637500
16.2%
: 337500
 
8.6%
, 300000
 
7.6%
y 187500
 
4.8%
a 150000
 
3.8%
d 150000
 
3.8%
0 135730
 
3.5%
2 118581
 
3.0%
1 116029
 
3.0%
Other values (21) 1122794
28.6%

review/timeUnix
Real number (ℝ)

Distinct37490
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2327936 × 109
Minimum9.262944 × 108
Maximum1.3262666 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:42.580933image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum9.262944 × 108
5-th percentile1.089043 × 109
Q11.1891944 × 109
median1.2481503 × 109
Q31.2913303 × 109
95-th percentile1.3194199 × 109
Maximum1.3262666 × 109
Range3.999722 × 108
Interquartile range (IQR)1.0213587 × 108

Descriptive statistics

Standard deviation71909548
Coefficient of variation (CV)0.058330564
Kurtosis0.03389237
Mean1.2327936 × 109
Median Absolute Deviation (MAD)47784583
Skewness-0.86216245
Sum4.6229762 × 1013
Variance5.1709831 × 1015
MonotonicityNot monotonic
2024-11-13T12:29:42.894749image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
926294401 3
 
< 0.1%
969580801 3
 
< 0.1%
1278875638 2
 
< 0.1%
1255108092 2
 
< 0.1%
1241043404 2
 
< 0.1%
1181754698 2
 
< 0.1%
955497601 2
 
< 0.1%
1268935767 2
 
< 0.1%
1269216814 1
 
< 0.1%
1234910269 1
 
< 0.1%
Other values (37480) 37480
99.9%
ValueCountFrequency (%)
926294401 3
< 0.1%
940723201 1
 
< 0.1%
955497601 2
< 0.1%
967852801 1
 
< 0.1%
969580801 3
< 0.1%
972000001 1
 
< 0.1%
988202869 1
 
< 0.1%
993251490 1
 
< 0.1%
994874122 1
 
< 0.1%
996506774 1
 
< 0.1%
ValueCountFrequency (%)
1326266601 1
< 0.1%
1326257441 1
< 0.1%
1326254548 1
< 0.1%
1326253848 1
< 0.1%
1326251875 1
< 0.1%
1326246991 1
< 0.1%
1326241506 1
< 0.1%
1326239004 1
< 0.1%
1326235817 1
< 0.1%
1326234528 1
< 0.1%

user/ageInSeconds
Real number (ℝ)

High correlation  Missing 

Distinct1471
Distinct (%)18.7%
Missing29644
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean1.1767051 × 109
Minimum7.0343665 × 108
Maximum3.6272954 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.1 KiB
2024-11-13T12:29:43.181601image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum7.0343665 × 108
5-th percentile8.5662385 × 108
Q19.7948105 × 108
median1.100009 × 109
Q31.2749726 × 109
95-th percentile1.7138846 × 109
Maximum3.6272954 × 109
Range2.9238588 × 109
Interquartile range (IQR)2.954916 × 108

Descriptive statistics

Standard deviation3.375514 × 108
Coefficient of variation (CV)0.2868615
Kurtosis20.514671
Mean1.1767051 × 109
Median Absolute Deviation (MAD)1.421244 × 108
Skewness3.5290889
Sum9.2441953 × 1012
Variance1.1394094 × 1017
MonotonicityNot monotonic
2024-11-13T12:29:43.451445image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1080572647 76
 
0.2%
1137506648 59
 
0.2%
1351346647 56
 
0.1%
1189001047 52
 
0.1%
1215788647 48
 
0.1%
905004248 48
 
0.1%
1579701848 47
 
0.1%
1301756647 45
 
0.1%
1244300647 42
 
0.1%
1378562647 40
 
0.1%
Other values (1461) 7343
 
19.6%
(Missing) 29644
79.1%
ValueCountFrequency (%)
703436648 2
< 0.1%
733071847 1
 
< 0.1%
733158247 1
 
< 0.1%
745427047 2
< 0.1%
751385047 1
 
< 0.1%
760802647 1
 
< 0.1%
762793447 1
 
< 0.1%
776271847 2
< 0.1%
782661847 4
< 0.1%
783266647 1
 
< 0.1%
ValueCountFrequency (%)
3627295447 25
0.1%
3594722648 2
 
< 0.1%
3581417047 35
0.1%
3527676247 3
 
< 0.1%
2577621848 5
 
< 0.1%
2366546647 9
 
< 0.1%
2356956247 1
 
< 0.1%
2234185447 12
 
< 0.1%
2233407847 2
 
< 0.1%
2202476647 1
 
< 0.1%

user/birthdayRaw
Date

Missing 

Distinct1432
Distinct (%)18.2%
Missing29644
Missing (%)79.1%
Memory size293.1 KiB
Minimum1900-01-01 00:00:00
Maximum1992-08-27 00:00:00
2024-11-13T12:29:43.721291image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:43.997117image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

user/birthdayUnix
Real number (ℝ)

High correlation  Missing 

Distinct1432
Distinct (%)18.2%
Missing29644
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean2.4163034 × 108
Minimum-2.20896 × 109
Maximum7.148988 × 108
Zeros0
Zeros (%)0.0%
Negative1202
Negative (%)3.2%
Memory size293.1 KiB
2024-11-13T12:29:44.269958image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-2.20896 × 109
5-th percentile-2.955492 × 108
Q11.433628 × 108
median3.183264 × 108
Q34.388544 × 108
95-th percentile5.617116 × 108
Maximum7.148988 × 108
Range2.9238588 × 109
Interquartile range (IQR)2.954916 × 108

Descriptive statistics

Standard deviation3.375514 × 108
Coefficient of variation (CV)1.3969744
Kurtosis20.514671
Mean2.4163034 × 108
Median Absolute Deviation (MAD)1.421244 × 108
Skewness-3.5290889
Sum1.898248 × 1012
Variance1.1394094 × 1017
MonotonicityNot monotonic
2024-11-13T12:29:44.537821image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
337762800 76
 
0.2%
280828800 59
 
0.2%
66988800 56
 
0.1%
229334400 52
 
0.1%
513331200 49
 
0.1%
202546800 48
 
0.1%
-161366400 47
 
0.1%
116578800 45
 
0.1%
174034800 42
 
0.1%
39772800 40
 
0.1%
Other values (1422) 7342
 
19.6%
(Missing) 29644
79.1%
ValueCountFrequency (%)
-2208960000 25
0.1%
-2176387200 2
 
< 0.1%
-2163081600 35
0.1%
-2109340800 3
 
< 0.1%
-1159286400 5
 
< 0.1%
-948211200 9
 
< 0.1%
-938620800 1
 
< 0.1%
-815850000 12
 
< 0.1%
-815072400 2
 
< 0.1%
-784141200 1
 
< 0.1%
ValueCountFrequency (%)
714898800 2
< 0.1%
685263600 1
 
< 0.1%
685177200 1
 
< 0.1%
672908400 2
< 0.1%
666950400 1
 
< 0.1%
657532800 1
 
< 0.1%
655542000 1
 
< 0.1%
642063600 2
< 0.1%
635673600 4
< 0.1%
635068800 1
 
< 0.1%

user/gender
Categorical

Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing22186
Missing (%)59.2%
Memory size293.1 KiB
Male
15069 
Female
 
245

Length

Max length6
Median length4
Mean length4.0319969
Min length4

Characters and Unicode

Total characters61746
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale

Common Values

ValueCountFrequency (%)
Male 15069
40.2%
Female 245
 
0.7%
(Missing) 22186
59.2%

Length

2024-11-13T12:29:44.830652image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T12:29:45.072514image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
male 15069
98.4%
female 245
 
1.6%

Most occurring characters

ValueCountFrequency (%)
e 15559
25.2%
a 15314
24.8%
l 15314
24.8%
M 15069
24.4%
F 245
 
0.4%
m 245
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46432
75.2%
Uppercase Letter 15314
 
24.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15559
33.5%
a 15314
33.0%
l 15314
33.0%
m 245
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
M 15069
98.4%
F 245
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 61746
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15559
25.2%
a 15314
24.8%
l 15314
24.8%
M 15069
24.4%
F 245
 
0.4%
m 245
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 15559
25.2%
a 15314
24.8%
l 15314
24.8%
M 15069
24.4%
F 245
 
0.4%
m 245
 
0.4%
Distinct7441
Distinct (%)19.8%
Missing5
Missing (%)< 0.1%
Memory size293.1 KiB
2024-11-13T12:29:45.394315image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.9179891
Min length3

Characters and Unicode

Total characters334380
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3157 ?
Unique (%)8.4%

Sample

1st rowRblWthACoz
2nd rowBeerSox
3rd rowmschofield
4th rowmolegar76
5th rowBrewbro000
ValueCountFrequency (%)
northyorksammy 141
 
0.4%
buckeyenation 110
 
0.3%
mikesgroove 92
 
0.2%
chaingangguy 84
 
0.2%
masterski 83
 
0.2%
akorsak 81
 
0.2%
oberon 81
 
0.2%
barleywinefiend 80
 
0.2%
thorpe429 79
 
0.2%
smcolw 74
 
0.2%
Other values (7431) 36590
97.6%
2024-11-13T12:29:46.043942image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 33831
 
10.1%
a 24520
 
7.3%
r 23730
 
7.1%
o 20078
 
6.0%
n 17823
 
5.3%
i 16652
 
5.0%
t 14681
 
4.4%
s 14104
 
4.2%
l 13104
 
3.9%
d 10506
 
3.1%
Other values (52) 145351
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 278753
83.4%
Uppercase Letter 31933
 
9.5%
Decimal Number 23694
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 33831
 
12.1%
a 24520
 
8.8%
r 23730
 
8.5%
o 20078
 
7.2%
n 17823
 
6.4%
i 16652
 
6.0%
t 14681
 
5.3%
s 14104
 
5.1%
l 13104
 
4.7%
d 10506
 
3.8%
Other values (16) 89724
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 4020
 
12.6%
S 2423
 
7.6%
D 2185
 
6.8%
M 2068
 
6.5%
T 1955
 
6.1%
C 1954
 
6.1%
G 1698
 
5.3%
J 1596
 
5.0%
A 1540
 
4.8%
R 1432
 
4.5%
Other values (16) 11062
34.6%
Decimal Number
ValueCountFrequency (%)
1 4238
17.9%
0 3080
13.0%
2 2940
12.4%
7 2424
10.2%
3 2231
9.4%
8 2038
8.6%
9 2003
8.5%
4 1734
7.3%
5 1660
 
7.0%
6 1346
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 310686
92.9%
Common 23694
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 33831
 
10.9%
a 24520
 
7.9%
r 23730
 
7.6%
o 20078
 
6.5%
n 17823
 
5.7%
i 16652
 
5.4%
t 14681
 
4.7%
s 14104
 
4.5%
l 13104
 
4.2%
d 10506
 
3.4%
Other values (42) 121657
39.2%
Common
ValueCountFrequency (%)
1 4238
17.9%
0 3080
13.0%
2 2940
12.4%
7 2424
10.2%
3 2231
9.4%
8 2038
8.6%
9 2003
8.5%
4 1734
7.3%
5 1660
 
7.0%
6 1346
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 334380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 33831
 
10.1%
a 24520
 
7.3%
r 23730
 
7.1%
o 20078
 
6.0%
n 17823
 
5.3%
i 16652
 
5.0%
t 14681
 
4.4%
s 14104
 
4.2%
l 13104
 
3.9%
d 10506
 
3.1%
Other values (52) 145351
43.5%

Interactions

2024-11-13T12:29:29.117593image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:01.036735image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:03.493325image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:06.159790image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:08.736311image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:11.164913image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:13.805412image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:16.339938image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:18.767560image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:21.310082image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:24.129476image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:26.651027image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:29.308499image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:01.261606image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:03.681233image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:06.366672image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:08.929215image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:11.356805image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:14.010277image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:16.533832image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:18.976425image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:21.516965image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:24.327345image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:26.833922image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:29.539366image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:01.450498image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:03.869125image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:06.571553image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:09.128084image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:11.551690image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:14.217161image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:16.733729image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:19.190319image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:21.719846image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:24.537243image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:27.040786image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:29.754244image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:01.663375image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:04.084001image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:06.799428image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:09.352957image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:11.758590image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:14.449025image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:16.936611image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:19.418185image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:21.940736image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:24.769091image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:27.259677image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:29.956112image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:01.855283image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:04.273880image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:06.992329image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:09.540850image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:11.953460image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:14.650948image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:17.130484image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:19.623053image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:22.407450image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:24.972991image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:27.451566image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:30.169988image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:02.042175image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:04.462784image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:07.212184image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:09.732738image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:12.137355image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:14.844800image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:17.311380image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:19.816938image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:22.627323image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:25.174861image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:27.656449image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:30.384863image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:02.253041image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:04.681657image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:07.441056image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:09.951612image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:12.348233image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:15.071667image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:17.524261image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:20.034831image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:22.851195image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:25.396732image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:27.873307image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:30.608752image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:02.467915image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:20.230702image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:28.089185image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:30.819630image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:02.684791image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:05.081413image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:07.869808image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:10.358394image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:12.767009image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:15.485430image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:17.922045image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:20.463584image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:31.042487image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:02.894667image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:05.291307image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:15.705320image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:20.687457image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:23.492826image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:03.102549image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:05.763036image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:08.318566image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:10.780151image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:13.386638image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:15.930190image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:18.341787image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:20.903330image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:26.256254image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:28.727815image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:31.453249image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:03.296436image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:05.955908image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:10.975024image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:16.139071image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:21.101201image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-11-13T12:29:26.457121image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-13T12:29:28.914708image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-11-13T12:29:46.254834image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
beer/ABVbeer/beerIdbeer/brewerIddf_indexreview/appearancereview/aromareview/overallreview/palatereview/tastereview/timeUnixuser/ageInSecondsuser/birthdayUnixuser/gender
beer/ABV1.0000.4030.159-0.1670.3100.4210.2190.3820.4000.235-0.1250.1250.000
beer/beerId0.4031.0000.499-0.3100.0220.0840.0020.0650.0590.392-0.0860.0860.000
beer/brewerId0.1590.4991.000-0.2690.0040.015-0.0140.0190.0020.199-0.0410.0410.020
df_index-0.167-0.310-0.2691.0000.0340.0220.0430.0200.029-0.1570.021-0.0210.024
review/appearance0.3100.0220.0040.0341.0000.4950.4600.5150.4930.060-0.0500.0500.006
review/aroma0.4210.0840.0150.0220.4951.0000.5590.5650.6710.100-0.0760.0760.007
review/overall0.2190.002-0.0140.0430.4600.5591.0000.6450.7210.058-0.0540.0540.000
review/palate0.3820.0650.0190.0200.5150.5650.6451.0000.6910.084-0.0800.0800.000
review/taste0.4000.0590.0020.0290.4930.6710.7210.6911.0000.086-0.0850.0850.020
review/timeUnix0.2350.3920.199-0.1570.0600.1000.0580.0840.0861.000-0.2770.2770.037
user/ageInSeconds-0.125-0.086-0.0410.021-0.050-0.076-0.054-0.080-0.085-0.2771.000-1.0000.033
user/birthdayUnix0.1250.0860.041-0.0210.0500.0760.0540.0800.0850.277-1.0001.0000.033
user/gender0.0000.0000.0200.0240.0060.0070.0000.0000.0200.0370.0330.0331.000

Missing values

2024-11-13T12:29:31.778079image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-13T12:29:32.417716image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-13T12:29:32.975451image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

df_indexbeer/ABVbeer/beerIdbeer/brewerIdbeer/namebeer/stylereview/appearancereview/aromareview/overallreview/palatereview/tastereview/textreview/timeStructreview/timeUnixuser/ageInSecondsuser/birthdayRawuser/birthdayUnixuser/genderuser/profileName
0401635.04663414338ChiostroHerbed / Spiced Beer4.04.04.04.04.0Pours a clouded gold with a thin white head. Nose is quite floral with a larger amount of spices added. Definitely a spice forward fragrance. Flavor has an odd burn that hits on the first sip. After it fades it seems like a dirty vanilla aftertaste. Perhaps this is the absinthe? Regardless of that, I get a quite spiced tone on the tongue. Almost feel a little heat from it. I think that my inexperienced palate on these spices is contributing to my ignorance of what precisely they are. Overall a nice drinker indeed.{'min': 38, 'hour': 3, 'mday': 16, 'sec': 10, 'year': 2008, 'wday': 1, 'mon': 12, 'isdst': 0, 'yday': 351}1229398690NaNNaNNaNNaNRblWthACoz
1813511.03003395Bearded Pat's BarleywineAmerican Barleywine4.03.53.53.53.012oz bottle into 8oz snifter.\t\tDeep ruby red hue with a one finger light tan head that settles to a thin rim along the glass.\t\tSharp piercing hops with some light hard candy in the background. \t\tThe hops provide some bitterness, but they aren't as sharp as I would have expected. Mostly a light candy flavor like in the aroma. Full bodied with good carbonation. The finish is some lingering sweet flavor with a bit of bitterness.\t\tA very sweet barleywine with a weird hard candy flavor that seemed to dominate. Not bad, but I would have liked a little more complexity.{'min': 38, 'hour': 23, 'mday': 8, 'sec': 58, 'year': 2008, 'wday': 4, 'mon': 8, 'isdst': 0, 'yday': 221}1218238738NaNNaNNaNNaNBeerSox
2105294.7961365Naughty Nellie's AleAmerican Pale Ale (APA)3.54.03.53.53.5First enjoyed at the brewpub about 2 years ago, I finally managed to get a bottle.\tSlightly hazy orange-amber topped with a two finger foamy white head.\tVery nice fruity aroma, soft and floral, tea and toast.\tFruity, slightly grapefruity hop note, toast and biscuity malt balance. Hoppier and more floral when it warms up.\tLight-medium bodied, liked it better on draft but still a solid beer.{'min': 7, 'hour': 18, 'mday': 26, 'sec': 2, 'year': 2004, 'wday': 4, 'mon': 11, 'isdst': 0, 'yday': 331}1101492422NaNNaNNaNMalemschofield
3446104.44291Pilsner UrquellCzech Pilsener3.03.02.53.03.0First thing I noticed after pouring from green bottle to glass was the skunky smell. Overpowering. Lacing was minimal and faded quickly. Bottle had exp date and was still within freshness date. \t\tTaste was like drinking a milwaukee's best with some skunk. Just couldn't get over the skunky smell to finish my second bottle. Almost $10 a sixer, I would have been better off getting Bud Light.{'min': 7, 'hour': 1, 'mday': 20, 'sec': 5, 'year': 2011, 'wday': 0, 'mon': 6, 'isdst': 0, 'yday': 171}13085320251.209827e+09Aug 10, 1976208508400.0Malemolegar76
4370624.449041417Black Sheep Ale (Special)English Pale Ale4.03.03.03.52.5A: pours an amber with a one finger head but only with a very strong pour, head recedes to a light layer of foam with some large bubbles and good lacing\tS: sweet caramel and bread from the English malts comes through, some mild fruityness on the back end\tT: not a lot of complexity with this for me. I didn't expect much considering the style but it's just bland and lacking more bready layers\tM/D: more carbonated than I would have wanted. I would expect this to be much better on cask{'min': 51, 'hour': 6, 'mday': 12, 'sec': 48, 'year': 2011, 'wday': 5, 'mon': 3, 'isdst': 0, 'yday': 71}1299912708NaNNaNNaNNaNBrewbro000
51409510.02143614YouEnjoyMyStoutRussian Imperial Stout4.04.04.04.04.5served in a snifter; on-tap at CBC.\t\tcolor is the typical imperial stout used motor oil black; impenetrable. by the time the beer arrived at our table the had had receded into a collar around the glass.\t\tnoses offers ample amounts of roastiness, chocolate, molasses and dark fruits, also an atypical tartness to it. not picking up much in the way of bourbon.\t\tflavor imparts more of the same: big notes of roasted malt with chocolate and molasses not far behind, also some dark fruit characters to it and a very distinct and unusual tartness, which adds almost a distinctive flair. more bourbon than i picked up in the aroma but still a subtle presence on that front. medium-full on the palate with average carbonation.\t\toverall a tasty and interesting beer. i like the unique element that the tartness bring; could use a bigger bourbon presence though. also priced very reasonably at $5.50 a glass.{'min': 16, 'hour': 1, 'mday': 20, 'sec': 9, 'year': 2011, 'wday': 1, 'mon': 12, 'isdst': 0, 'yday': 354}1324343769NaNNaNNaNNaNperrymarcus
61375912.61000114BenevolenceAmerican Wild Ale4.04.54.04.04.0my 100th review on-tap! mini snifter\t\t A nutty dark brown color, thin and tanned head with only small lacing all around. \t\t the nose has a fruity, sour and wild yeast aroma up-front. solid, thick and sweet malt underneath, dark fruits, dates and raisins and very tart. \t\t the flavor is a very nice wild-yeast complexity that has tangy and sweet dark fruits, wood-aged alcohol effect along side with a very solid malty balance. wonderful complexity for this wild ale, slightly peppery and herbal on the way down. sour-cherry flavor makes this one really refreshing. Oak and vanilla pop out of the malt in a subtle way and the very end bringa a port wine sweetness.\t\t this one has wonderful balance for a wild yeast ale.{'min': 1, 'hour': 18, 'mday': 8, 'sec': 12, 'year': 2009, 'wday': 0, 'mon': 6, 'isdst': 0, 'yday': 159}1244484072NaNNaNNaNNaNGratefulBeerGuy
739148.45221114879Frog's Hollow Double Pumpkin AlePumpkin Ale4.04.04.04.04.0One of the better pumpkin ales I've tried so far. Not as imperialized as it may suggest but very nicely balanced and quaffable.\t\tPresentation: 22 oz brown capped bottle. Label pivoting around the image of a standing/hopping frog holding a jar of beer (amber-pumpkin on this version). Perfunctorily terribly designed label with assorted fonts and the standard awful array of blends and color effects with the added novelty of... A picture of the moon under the glow of the name? Side paragraphs offer a general description of the brew, and intent. Lacks any bottling or freshness date. Notes Alc. by Vol. (8.4%), IBUs (7.3), and OG (76). Served in a snifter. \t\tA - Medium amber to orange pumpkin color with a nice creamy head that fades quickly leaving a fair surface memory.\t\tS - Well balanced nose with a characteristic pumpkin sense, sweet and riding on a nice gamut of spices. Good balance, although a bit less and it would be short, hitting the right note with some risk.\t\tT - Follows nicely the smell with a good malt backbone woven with pumpkin and a rich balance of spices complementing the brew.\t\tM - Medium to medium-light body, medium prickly carbonation, finely tuned.\t\tD - Deceptively quaffable given the alcohol bill, which is rather well integrated. Nice pumpkin ale.\t\tNotes: Sure, this could do with an additional hefty note and still be quite notable as a pumpkin ale, but in this incarnation it feels very well rounded, so why touch it?{'min': 32, 'hour': 20, 'mday': 9, 'sec': 40, 'year': 2010, 'wday': 5, 'mon': 10, 'isdst': 0, 'yday': 282}1286656360NaNNaNNaNNaNDaniellobo
8479539.034361394Stoudt's Barrel Aged Old AbominableEnglish Barleywine4.54.04.54.54.5A snifter filled (several times over) from a 750ml bottle; I pulled this from the dusty clutches of the cellar, a bottle saved for 3+ years from one of my earliest trades. Needed a strong SEPA brew to soften the shocking blow that comes with learning that one of my best friends from high school died today (he was killed by a car while riding his bike in his adopted hometown of Philly ~ a toast to Russ). \t\tThe goofy 'Abominable' cartoon made me smile on an otherwise somber day...\t\tA: Lovely and leathery, an alluring chestnut/garnet, barely translucent. No signs of yeasty bits nor other fatigue from the years in captivity. Starts with about a finger of fizzy but firm khaki cream. A slow droop, then a small break in the topping, then a crescent ring. Slick speckles of lace.\t\tS: Sweet and nutty, toffee and candied fruit - er, fruitcake. A 'buttered rum' quality, but little notable woody/oaky aroma.\t\tT: The requisite toffee, mellowed fruit form a dreamy, dessert-worthy concoction. A little butterscotch (or creme brulee?). Fruity apple pie, something a little brandy-like. Oak, though tame, still holds a fair vanilla bean and charred woodiness. Very well balanced.\t\tM: Velvet, pure velvet...sweetly coating. Modest carbonation and trace amounts of lip-smacking stickiness. Medium thickness. Easy on the tongue, as they say...\t\tD: Love the beer, hate the occasion for opening it. Definitely worth saving, as it's damn delicious and oh so drinkable. Wish I had another; cherish it while you can. That goes for beer and life, both.\t\tThanks to zrrbrrt/jyoungsbcp, aka Josh for sending way back when...{'min': 26, 'hour': 3, 'mday': 16, 'sec': 13, 'year': 2010, 'wday': 4, 'mon': 7, 'isdst': 0, 'yday': 197}1279250773NaNNaNNaNMalemsubulldog25
970476.2326761386One Hop Wonder IPAAmerican IPA2.02.02.02.52.0Brewed with five hop additions, this alleged IPA has a slight cidery aroma, zero carbonation, and not a shred of head or lace. It is simple, clear amber.\t\t\tUnfortunately, Harmon really dropped the ball on this fall seasonal. It is green tasting and oddly devoid of even the slightest hop aroma. The 68 IBUs of Glacier hops really dont shine, making this hard to reconcile as a single hop showcase beer. One Hop Wonder is not a completely disastrous ale, but the body is lifeless and the beer remains conceptually undeveloped. Nothing in the taste or aroma remotely resemble an IPA. It tastes like tired yeasts unable to pull their weight, and the finish is deathly. \t\t\tNot up to Harmon standards.{'min': 26, 'hour': 5, 'mday': 16, 'sec': 41, 'year': 2006, 'wday': 0, 'mon': 10, 'isdst': 0, 'yday': 289}1160976401NaNNaNNaNNaNRedDiamond
df_indexbeer/ABVbeer/beerIdbeer/brewerIdbeer/namebeer/stylereview/appearancereview/aromareview/overallreview/palatereview/tastereview/textreview/timeStructreview/timeUnixuser/ageInSecondsuser/birthdayRawuser/birthdayUnixuser/genderuser/profileName
37490465205.001550394Stoudts American Pale AleAmerican Pale Ale (APA)3.03.54.03.03.5Light amber color, slightly sweetish fruity nose.\t\tVery smooth and clean taste, with some malty sweetness balanced quite well with some flowery hop notes. Super easy to drink. Not overly full bodied, but still a certain richness. You can tell it has a lot of quality brewed into it. My first Stoudt's product and one that impressed me enough to definitely try the others.{'min': 56, 'hour': 12, 'mday': 22, 'sec': 16, 'year': 2002, 'wday': 4, 'mon': 2, 'isdst': 0, 'yday': 53}10143825761.344006e+09May 10, 197274329200.0Malebmills1608
37491226699.20258521199Founders Blushing MonkBelgian Strong Pale Ale4.04.54.54.54.512 oz bottle poured at Belgique tasting, Hugo MN Thanksgiving 2010.\t\tDark ruby brew. Fine bubbles. Delicious tangy raspberry aroma, with an earthy leaf must underlying. Tart and extreme raspberry...incredible lack of any alcohol heat given the greater than 12% ABV. Brett provides a mushroomy flavor. A rich maltiness and slick and sticky mouthfeel. Truly a unique and fabulous brew!{'min': 5, 'hour': 3, 'mday': 19, 'sec': 56, 'year': 2011, 'wday': 1, 'mon': 4, 'isdst': 0, 'yday': 109}13031823561.497453e+09Jun 30, 1967-79117200.0Malekenito799
3749236946.803362414879Hoppin' To Heaven IPAAmerican IPA3.03.53.53.03.0Received from nlmartin. Thanks!\t\tFizzy off-white head composed of large bubbles. Reduced to a soapy layer that eventually disappeared. Clear, light copper color.\t\tCaramel and some sweet bread malts in the nose. Mostly citrus hops with some bordering on tropical with some bubble gum and raw sugar. Fairly strong, but quite simple.\t\tPretty well balanced. Has a grainy, bread-like malt base. Citrusy hops and some piney notes. Hops are nearly as pronounced as the nose would suggest. Little hints of alcohol.\t\tBody is a bit thin really with low carbonation. Overall seems a bit watery. Flavor lingers for a bit after the swallow.\t\tDrinkability...ehh. Nothing overly noteworthy, but it goes down easy and it does taste like beer. Nothing wrong with it, just mediocre.{'min': 18, 'hour': 0, 'mday': 16, 'sec': 46, 'year': 2007, 'wday': 5, 'mon': 6, 'isdst': 0, 'yday': 167}11819531261.021216e+09Aug 2, 1982397119600.0Maleblitz134
374933288511.20199601199Founders KBS (Kentucky Breakfast Stout)American Double / Imperial Stout4.02.02.51.02.0Tried a 2011 bottle on May 15 with two of my friends on our "Epic Beer Tasting Day". The line-up consisted of 2010 Darklord, Rare Bourbon County Stout, , 2011 Hanahpu, 2011 KBS, 2010 Abyss.\t\tAppearance - It pours a very dark brown, almost black in appearance. Had a very thin mocha colored head that quickly disappears.\t\tSmell - Bourbon? Nope I didn't smell any of that. I smelled mostly burnt coffee/caramel and nothing else. Disappointing to say the least. \t\tTaste - The alcohol is just too overwhelming in this. I couldn't taste anything but alcohol. I thought it would have a wonderful balanced flavor of coffee, chocolate, vanilla, and bourbon, but got nothing of it.\t\tMouthfeel - Very thick as it coats your whole mouth and burns your throat as it goes down. Not a pleasant experience at all.\t\tOverall - Overrated! Very disappointed.{'min': 44, 'hour': 4, 'mday': 21, 'sec': 19, 'year': 2011, 'wday': 5, 'mon': 5, 'isdst': 0, 'yday': 141}1305953059NaNNaNNaNMaledvsbizzyb
37494119437.506484824447Li'l NapoleonAmerican IPA4.03.54.54.04.5I had a pint of this at Hopjacks Pizza Kitchen & Taproom on Sunday, September 25, 2011. I specify the date as this beer was phenomenal. I have had it in the past but is seems that this new brewery had hit the nail on the head and perfected its recipe. \t\tA: nice hazy golden color with nice head that stuck around for awhile, good lacing on the glass.\t\tS: this is always my weakest review as I typically have stuffed sinuses...some detections of citrus, hops, wheat.\t\tT: delicious, this rivals some very well known IPAs and is on point for an IPA as far as style characteristics. Had the citrus peel/grapefruit flavor, lots of hops, spices nice refreshing drink.\t\tM: I had ridden my bicycle to the pub and needed a refreshing drink, this hit the spot. Crisp, full of effervescence. \t\tOverall: I have had this beer several times now and this was the best batch thus far. Hope the brewery will be consistent as this could be the beer that launches a thousand barrels. Also hope they start bottling soon. Great job guys.{'min': 21, 'hour': 16, 'mday': 26, 'sec': 21, 'year': 2011, 'wday': 0, 'mon': 9, 'isdst': 0, 'yday': 269}1317054081NaNNaNNaNFemaleabeerlovr
37495351755.50224503268Blackberry Scottish-StyleFruit / Vegetable Beer4.03.53.53.53.512 oz brown longneck with no freshness dating.\t\tPoured in my SA pint glass, the beer is a hazy brown with gold highlights. There is a huge beige head & decent lacing.\t\tThe aroma is of smoky malts, some berries and brown sugar.\t\tFirst taste is berries followed rapidly by the peaty malts. The berries flavor is neither overwhelming or artificial. More berries in the aftertaste and the beer sweetens. I'd like a little more robust scotch ale as the base for this one. \t\tThe mouth is solid. Drinkablity is tougher. Would I drink all night, no. Would I drink occasionally, yes. Interesting combo is worth searching out.{'min': 56, 'hour': 23, 'mday': 10, 'sec': 1, 'year': 2008, 'wday': 3, 'mon': 4, 'isdst': 0, 'yday': 101}1207871761NaNNaNNaNNaNRedrover
37496236668.5074631199Founders Dirty BastardScotch Ale / Wee Heavy4.54.03.54.54.5A - A bright red with a maroon-amber hue; minimal light tan head but it has very good lacing.\t\tS - Just a great aroma; smells of plum, dark cherry in their purest form; malt and chocolate; molasses/brown sugar smell aroma; you can smell the alcohol.\t\tT - Taste follows the nose and more. Strong flavor of dark fruits that are sugary and coated. A little bit yeasty. A nice hop effect that is pleasantly surprising for this style. Scotchy alcoholic aftertaste. This is a great scotch ale. \t\tM - Excellent. Whole; the sticky head accompanies each sip with an exceptional swallow. Low to medium carbonation. \t\tD - Drinkable but it has a high ABV and is pretty heavy. Two of these and you'll be good for the night. I wouldn't call it sessionable, therefore. \t\tOne of the best beers I've had to date. This is a style I'm pretty unfamiliar with in my young beer drinking days, but this shit is TASTY!{'min': 45, 'hour': 5, 'mday': 10, 'sec': 14, 'year': 2010, 'wday': 6, 'mon': 1, 'isdst': 0, 'yday': 10}1263102314NaNNaNNaNNaNjmerloni
37497477204.751154394Stoudt's FestMärzen / Oktoberfest4.03.54.04.54.0Sampled on tap at Redbones.\t\tThis marzen style beer poured a clear, copper color with white foam that settled. The smell was a mild, slightly sweet malty aroma. The taste was slightly sweet (but less sweet than many other of this style) and tangy, malty, with the hops making their presence felt in the finish. There was also a bit of a dry, oaky flavor. The mouthfeel was smooth and creamy up front, but with a dry finish. The body and carbonation were medium. The aftertaste was dry and lingered nicely. This was a good oktoberfest beer.{'min': 3, 'hour': 1, 'mday': 25, 'sec': 36, 'year': 2003, 'wday': 5, 'mon': 10, 'isdst': 0, 'yday': 298}1067043816NaNNaNNaNNaNUncleJimbo
374983323311.20199601199Founders KBS (Kentucky Breakfast Stout)American Double / Imperial Stout4.04.04.05.05.0Pours a black body with a brown head that very quickly fizzles away to a thin brown lace.\t\tAroma smells of coffee beans, bourbon, chocolate, malt.\t\tTaste a lot of bourbon and coffee right off the bat. Then, hints of chocolate and something very sweet like a syrup. After letting the beer settle I find the flavors come more together as it warms up. An incredibly tasty stout.\t\tMouthfeel is very impressive. Thick, but not too thick with a velvet like feel.\t\tThis beer is heavy and fills you up, also 11.20% so its not a beer you need to drink a whole lot of. Still though, you might find it hard to pass up another glass.\t\tOverall this beer is one of the best stouts i'm yet to have.{'min': 52, 'hour': 19, 'mday': 29, 'sec': 33, 'year': 2011, 'wday': 5, 'mon': 1, 'isdst': 0, 'yday': 29}1296330753NaNNaNNaNNaNStockfan42
37499237588.5074631199Founders Dirty BastardScotch Ale / Wee Heavy4.04.04.04.54.0A nice sweet, malty beer...nothing complex, just a smooth refreshing drink that reveals no hint of 8.3 abv.\t\tPours an ice-tea colored brown. If held to the light, the very center of the beer is dense. Lots of light comes through on the sides. Tan head is average size with poor retention. Good lacing. Smell and taste are of caramel malts. Must be balanced very well because it is quite sweet but not cloying or too sweet for mass consumption. Mouthfeel is thick and rich. Drinkability is good. I finished off the 12 oz bottle quickly and could have enjoyed more.\t\tThis is one you have to be in the mood for, but if you are looking for something well made and sweet, this will do it for you.{'min': 40, 'hour': 18, 'mday': 4, 'sec': 28, 'year': 2009, 'wday': 4, 'mon': 9, 'isdst': 0, 'yday': 247}1252089628NaNNaNNaNNaNJayQue